Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Feature
  • Published:

What impact could artificial intelligence have on oral surgery in the next five years?

BDJ In Practice volume 37, pages 418–420 (2024)Cite this article

By Rachel Sladden, Specialty Dentist in Paediatric Dentistry, University Hospitals Bristol and Weston NHS Foundation Trust

Artificial intelligence (AI) encompasses the theory and development of computer systems capable of intellectual tasks typically performed by humans, requiring decision-making, learning, and problem-solving. Emerging in the 1950s, this is a rapidly progressing field and the release of freely accessible AI language modelling software, such as ChatGPT, are quickly making AI a part of daily life.1,2 The first healthcare application of AI incorporated a rule-based system to distinguish various infections in the 1980s.1 AI's ability to learn, classify and subsequently predict and detect pathology elicits a transition away from human, heuristic reasoning which is often biased and thus potentially erroneous.3,4

This is a preview of subscription content, access via your institution

Access options

Fig. 1

References

  1. Rokhshad R, Keyhan S O, Yousefi P. Artificial intelligence applications and ethical challenges in oral and maxillo-facial cosmetic surgery: a narrative review. Maxillofac Plast Reconstr Surg 2023; 45: 14.

  2. Dave M, Patel N. Artificial intelligence in healthcare and education. Br Dent J 2023; 234: 761-764.

  3. Rasteau S, Ernenwein D, Savoldelli C, Bouletreau P. Artificial intelligence for oral and maxillo-facial surgery: A narrative review. J Stomatol Oral Maxillofac Surg 2022; 123: 276-282.

  4. Renton T, Patel V. Oral surgery: what challenges and opportunities are there on the horizon?. Dent Update 2023; 50: 422-430.

  5. Van der Cruyssen F, Verhelst P J, Jacobs R. The Use of Artificial Intelligence in Third Molar Surgery Risk Assessment. Dent Update 2024; 51: 28-33.

  6. Schwendicke F A, Samek W, Krois J. Artificial intelligence in dentistry: chances and challenges. J Dent Res 2020; 99: 769-774.

  7. Vranckx M, Van Gerven A, Willems H, et al. Artificial intelligence (AI)-driven molar angulation measurements to predict third molar eruption on panoramic radiographs. Int J Environ Res Public Health 2020; 17: 3716.

  8. Eschert T, Schwendicke F, Krois J, Bohner L, Vinayahalingam S, Hanisch M. A survey on the use of artificial intelligence by clinicians in dentistry and oral and maxillofacial surgery. Medicina 2022; 58: 1059.

  9. Hur S H, Lee E Y, Kim M K, Kim S, Kang J Y, Lim J S. Machine learning to predict distal caries in mandibular second molars associated with impacted third molars. Sci Reports 2021; 11: 15447.

  10. Zhang W, Li J, Li ZB, Li Z. Predicting postoperative facial swelling following impacted mandibular third molars extraction by using artificial neural networks evaluation. Sci Reports 2018; 8: 12281.

  11. Miragall M F, Knoedler S, Kauke-Navarro M, et al. Face the Future - Artificial Intelligence in Oral and Maxillofacial Surgery. J Clin Med 2023; 12: 6843.

  12. World Health Organisation. World Health Statistics. 2022. Available from: https://www.who.int/data/gho/data/themes/world-health-statistics (accessed September 2024).

  13. Shan T, Tay FR, Gu L. Application of artificial intelligence in dentistry. J Dent Res 2021; 100: 232-244.

  14. Fiske A, Henningsen P, Buyx A. Your robot therapist will see you now: ethical implications of embodied artificial intelligence in psychiatry, psychology, and psychotherapy. J Med Internet Res 2019; 21: e13216.

  15. Pauwels R, Del Rey Y C. Attitude of Brazilian dentists and dental students regarding the future role of artificial intelligence in oral radiology: a multicentre survey. Dentomaxillofac Radiol 2021; 50: 20200461.

  16. Muehlematter U J, Daniore P, Vokinger K N. Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis. Lancet Digital Health 2021; 3: e195-203.

  17. Maitland A, Fowkes R, Maitland S. Can ChatGPT pass the MRCP (UK) written examinations? Analysis of performance and errors using a clinical decision-reasoning framework. BMJ Open 2024; 14: e080558.

  18. Recht M, Bryan R N. Artificial intelligence: threat or boon to radiologists?. J Am Coll Radiol 2017; 14: 1476-1480.

Download references

Author information

Authors and Affiliations

  1. University Teaching Hospital NHS Foundation Trust Bristol and Weston, Bristol, United Kingdom

    Rachel Sladden

Authors
  1. Rachel Sladden
    View author publications

    Search author on:PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sladden, R. What impact could artificial intelligence have on oral surgery in the next five years?. BDJ In Pract 37, 418–420 (2024). https://doi.org/10.1038/s41404-024-2912-6

Download citation

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41404-024-2912-6

This article is cited by

Search

Advanced search

Quick links